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Abstract This article investigates the fuel savings potential of a series hybrid military truck using a simultaneous battery pack design and powertrain supervisory control optimization algorithm. The design optimization refers to the sizing of the lithium-ion battery pack in the hybrid configuration. The powertrain supervisory control optimization determines the most efficient way to split the power demand between the battery pack and the engine. Despite the available design and control optimization techniques, a generalized mathematical formulation and solution approach for combined design and control optimization is still missing in the literature. This article intends to fill that void by proposing a unified framework to simultaneously optimize both the battery pack size and power split control sequence. This is achieved through a combination of genetic algorithm (GA) and Pontryagin’s minimum principle (PMP) where the design parameters are integrated into the Hamiltonian function.

Investigating the impact of Gasoline fuel on diesel engine performance and emission is very important for military heavy- duty combat vehicles. Gasoline has great potential as alternative fuel due to rapid depletion of petroleum reserves and stringent emission legislations, under multi fuel strategy program for military heavy- duty combat vehicle. There is a known torque, horsepower and fuel economy penalty associated with the operation of a diesel engine with Gasoline fuel. On the other hand, experimental studies have suggested that Gasoline fuel has the potential for lowering exhaust emissions, especially NOx, CO, CO2, HC and particulate matter as compared to diesel fuel. Recent emission legislations also restrict the total number of nano particles emitted in addition to particulate matter, which has adverse health impact.

This Aerospace Standard (AS) is to be used as a supplement to SAE AS7109. In addition to the requirements contained in AS7109, the requirements contained herein shall apply to suppliers seeking NADCAP Coatings accreditation who are engaged in thermal spray.

Abstract The objective of this article is to evaluate the effects of different blast protective modules to military vehicle structures and occupants. The dynamic responses of the V-shape integral basic armor, the add-on honeycomb sandwich structure module, and the anti-shock seat-dummy system were simulated and analyzed. The improvements of occupant survivability by different protective modules were compared using occupant injury criteria. The integral armored cab can maintain the integrity of the cab body structure. The add-on honeycomb sandwich armor reduces the peak structural deformation and velocity of the cab floor by 34.9% and 47.4%, respectively, compared with the cab with integral armors only. The integral armored cab with the anti-shock seat or the honeycomb sandwich structures reduces the occupant shock responses below the injury criteria. For different blast threat intensities, the selection of appropriate protective modules can meet protection requirements.

Abstract Autonomy has the potential to make the most radical impact by significantly reducing the number of soldiers in harm’s way and changing the military paradigm. Benefits of autonomy to improve the Army’s mission capabilities and the rapid evolution of military systems exerts pressure to develop these systems quickly. Since the associated technological development is highly fast paced and stochastic, approaches that develop systems for stochastic future scenarios are required. In this article we present a vision for the autonomous high-mobility military systems for that future. We discuss the ramifications of autonomy in five areas: (1) fleet organization, (2) physical attributes of high-mobility military systems, (3) individual behaviors of autonomous assets, (4) interactions between humans and autonomous systems, and (5) operation and teaming strategies. We present the future vision, implications, requirements, and technological challenges for each of the five areas.

Abstract The advancement in vision sensors and embedded technology created the opportunity in autonomous vehicles to look ahead in the future to avoid potential obstacles and steep regions to reach the target location as soon as possible and yet maintain vehicle safety from rollover. The present work focuses on developing a nonlinear model predictive controller (NMPC) for a high-speed off-road autonomous vehicle, which avoids undesirable conditions including stationary obstacles, moving obstacles, and steep regions while maintaining the vehicle safety from rollover. The NMPC controller is developed using CasADi tools in the MATLAB environment. The CasADi tool provides a platform to formulate the NMPC problem using symbolic expressions, which is an easy and efficient way of solving the optimization problem. In the present work, the vehicle lateral dynamics are modeled using the Pacejka nonlinear tire model.

This Aerospace Standard (AS) is to be used as a supplement to SAE AS7109. In addition to the requirements contained in AS7109, the requirements contained herein shall apply to suppliers seeking NADCAP Coatings accreditation who are engaged in stripping of coated material.

Abstract In this article, a formation flying technique designed for a multiple unmanned aerial vehicles (multi-UAV) system to provide low-cost and efficient solution for civilian and military applications is presented. First, a modular leader-follower formation algorithm was developed to accomplish the formation flying with off-the-shelf low-cost components and sensors. Second, a proportional-integral-derivative (PID) controller was utilized for velocity control of the UAVs to maintain the tight formation. Third, a particle swarm optimization-optimized reciprocal velocity obstacles (PSO-RVO) algorithm was utilized for obstacles avoidance and collision avoidance between the UAVs while navigating, with the aid of sonar ranging sensors onboard. The formation flying algorithm developed was tested through both simulation and experiment using two quadcopters with global positioning system (GPS) signals.

Abstract Presently, 270 V direct current (DC) systems replace older 28 V DC voltage systems in both the civil and military aviation industry due to the requirement for more electrical power needs on board. Therefore, the existing avionics require retrofitting. The conversion from 270 V to 28 V appears to be quite promising for both old and new systems. This study aims to design an interleaved synchronous modular buck converter topology as a candidate for these requirements. Calculations for the converter design are conducted considering aviation standards. Switching with pulse-width modulation (PWM) is used to control the power converter. A double-loop feedback control system based on voltage and current feedback is designed. Therefore, the buck converter circuit with 1145 W power output is proposed, which supplies a 28 V and 41 A DC output from a 270 V DC input. The concept is verified using simulations and hardware-in-the-loop (HIL) experimental results.

The objective of this study was to optimize the occupant restraint systems for a light tactical vehicle in frontal crashes. A combination of sled testing and computational modeling were performed to find the optimal seatbelt and airbag designs for protecting occupants represented by three size of ATDs and two military gear configurations. This study started with 20 sled frontal crash tests to setup the baseline performance of existing seatbelts, which have been presented previously; followed by parametric computational simulations to find the best combinations of seatbelt and airbag designs for different sizes of ATDs and military gear configurations involving both driver and passengers. Then 12 sled tests were conducted with the simulation-recommended restraint designs. The test results were further used to validate the models. Another series of computational simulations and 4 sled tests were performed to fine-tune the optimal restraint design solutions.

Facial recognition software (FRS) is a form of biometric security that detects a face, analyzes it, converts it to data, and then matches it with images in a database. This technology is currently being used in vehicles for safety and convenience features, such as detecting driver fatigue, ensuring ride share drivers are wearing a face covering, or unlocking the vehicle. Public transportation hubs can also use FRS to identify missing persons, intercept domestic terrorism, deter theft, and achieve other security initiatives. However, biometric data is sensitive and there are numerous remaining questions about how to implement and regulate FRS in a way that maximizes its safety and security potential while simultaneously ensuring individual’s right to privacy, data security, and technology-based equality.

As powertrain hybridization technologies are becoming popular, their application for heavy-duty military vehicles is drawing attention. An intelligent design and operation of the energy management system (EMS) is important to ensure that hybrid military vehicles can operate efficiently, simultaneously maximize fuel economy and minimize monetary cost, while successfully completing mission tasks. Furthermore, an integrated EMS framework is vital to ensure a functional vehicle power system (VPS) to survive through critical missions in a highly stochastic environment, when needed. This calls for situational awareness and dynamic system reconfiguration capabilities on-board of the military vehicle. This paper presents a new energy management and control (EMC) framework based on holistic situational awareness (SA) and dynamic reconfiguration of the VPS.

Tradespace analysis is used to define the characteristics of the solution space for a vehicle design problem enabling decision-makers (DMs) to evaluate the risk-benefit posture of a vehicle design program. The tradespace itself is defined by a set of functional objectives defined by vehicle simulations and evaluating the performance of individual design solutions that are modeled by a set of input variables. Of special interest are efficient design solutions because their perfomance is Pareto meaning that none of their functional objective values can be improved without decaying the value of another objective. The functional objectives are derived from a combination of simulations to determine vehicle performance metrics and direct calculations using vehicle characteristics. The vehicle characteristics represent vendor specifications of vehicle subsystems representing various technologies.

This paper investigates the fuel saving potential of a series hybrid military truck using a simultaneous battery pack design and powertrain supervisory control optimization algorithm. The design optimization refers to the sizing of the Lithium-ion battery pack in the hybridized configuration. On the other hand, the powertrain supervisory control optimization finds the most efficient way to split power demands between the battery pack and the engine. Most of the previous literatures implement them separately. In contrast, combining the sizing and energy management problem into a single optimization problem produces the global optimal solution. This study proposes a novel unified framework to couple Genetic Algorithm (GA) with Pontryagin’s Minimum Principle (PMP) to determine the battery pack sizing and the power split control sequence simultaneously.

Thermal Management Techniques in Avionics Cooling Curing the Porosity Problem in Additive Manufacturing Space-Qualified Crystal Oscillators Reimagining Automated Test During a Pandemic EW: New Challenges, Technologies, and Requirements Software Enables New-Age, Flexible Test Solution for Analog and Digital Radios Formal Process Modeling to Improve Human-Decision-Making During Test and Evaluation Range Control Using the Innoslate software tool to formally model the process of conducting test range events can expose previously overlooked ambiguities and identify high-value decision points? Test and Evaluation of Autonomy for Air Platforms Tools, approaches, and insights to confidently approach the safe, secure, effective, and efficient testing of autonomy on air platforms.

Abstract Introduction: The use of less lethal impact munitions (LLIMs) by law enforcement has increased in frequency, especially following nationwide protests regarding police brutality and racial injustice in the summer of 2020. There are several reports of the projectiles causing severe injuries when they penetrate the skin including pulmonary contusions, bone fractures, liver lacerations, and, in some cases, death. The penetration threshold of skin in different body regions is due to differences in the underlying structure (varying degree of muscle, adipose tissue, and presence or absence of bone). Objective: The objective of this study was to further investigate what factors affected the likelihood of skin penetration in various body regions and to develop corresponding penetration risk curves.

Success in metal additive manufacturing (AM) relies on the optimization of a large set of process parameters to achieve materials whose properties and performance meet design and safety requirements. Despite continuous improvements in the process over the years, the quality of AM parts remains a major concern for manufacturers. Today, researchers are starting to move from discrete geometry-dependent build parameters to continuously variable or dynamically changing parameters that are geometry- and scan-path aware. This approach has become known as “feedforward control.” Process Control for Defect Mitigation in Laser Powder Bed Fusion Additive Manufacturing discusses the origins of feedforward control, its early implementations in AM, the current state of the art, and a path forward to its broader adoption. Click here to access the full SAE EDGETM Research Report portfolio.

During Operation Iraqi Freedom and Operation Enduring Freedom, improvised explosive devices were used strategically and with increasing frequency. To effectively design countermeasures for this environment, the Department of Defense identified the need for an under-body blast-specific Warrior Injury Assessment Manikin (WIAMan). To help with this design, information on Warfighter injuries in mounted under-body blast attacks was obtained from the Joint Trauma Analysis and Prevention of Injury in Combat program through their Request for Information interface. The events selected were evaluated by Department of the Army personnel to confirm they were representative of the loading environment expected for the WIAMan. A military case review was conducted for all AIS 2+ fractures with supporting radiology. In Warfighters whose injuries were reviewed, 79% had a foot, ankle or leg AIS 2+ fracture. Distal tibia, distal fibula, and calcaneus fractures were the most prevalent.

The EuroSID-2re (ES-2re) Anthropomorphic Test Device (ATD) commonly known as the crash test dummy is also used in the military domain to assess the risk of injury of armored vehicles occupants from lateral impact. The loading conditions range from low velocity - long duration impacts (4 m/s - 50 ms) similar to the automotive domain, to high velocity - short duration impacts (28 m/s - 3 ms) corresponding to cases where the panel deforms under an explosion. The human shoulder response to lateral impact was investigated at bounds of the loading condition spectrum previously mentioned, and also at intermediate conditions (14 m/s - 9 ms) in previous studies. The aim of the current study is to provide additional insight at the intermediate loading conditions which are not found in the literature.

Under body blast (UBB) loading to military transport vehicles is known to cause foot-ankle fractures to occupants due to energy transfer from the vehicle floor to the feet of the soldier. The soldier posture, the proximity of the event with respect to the soldier, the personal protective equipment (PPE) and age/sex of the soldier are some variables that can influence injury severity and injury patterns. Recently conducted experiments to simulate the loading environment to the human foot/ankle in UBB events (~5ms rise time) with variables such as posture, age and PPE were used for the current study. The objective of this study was to determine statistically if these variables affected the primary injury predictors, and develop injury risk curves. Fifty below-knee post mortem human surrogate (PMHS) legs were used for statistical analysis. Injuries to specimens involved isolated and multiple fractures of varying severity.